In this Season 3 episode, we break down a frustrating TikTok pattern: your video receives early engagement — likes, comments, even decent watch time — but then suddenly stops appearing on the For You Page. What causes distribution to stall after a promising start?

Emily explains how TikTok’s multi-stage testing system works, and why initial engagement alone isn’t enough to sustain expansion. The algorithm evaluates relative performance, comparing your content to other videos shown to the same audience cluster. If retention, rewatch rate, or engagement velocity drops below benchmark thresholds, scaling can slow quickly.

This episode clarifies the difference between early interaction and sustained performance, and addresses common misconceptions about shadowbanning. Season 5 allows for a structured analysis of distribution cycles and how creators can refine hooks, pacing, and audience alignment to improve scaling consistency.

If your videos show early promise but fail to expand, this conversation focuses on diagnosing retention patterns instead of reacting emotionally. Sustainable visibility depends on understanding how each evaluation stage works — and optimizing for the metrics that actually drive reach.

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